Une histoire de la conjecture de Gessel (en combinatoire … · Context and statement of Gessel’s...
Transcript of Une histoire de la conjecture de Gessel (en combinatoire … · Context and statement of Gessel’s...
Une histoire de la conjecture de Gessel(en combinatoire enumerative)
Kilian Raschel
Travail commun avec A. Bostan & I. Kurkova
Seminaire de combinatoire du LIX7 mai 2014
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
Since when do we count paths?
. Chevalier de Mere’s problemL’impatience me prend aussi bien qu’a vous et, quoique je sois encoreau lit, je ne puis m’empecher de vous dire que [. . . ]. Voici a peu prescomme je fais pour savoir la valeur de chacune des parties, quanddeux joueurs jouent, par exemple, en trois parties, et chacun a mis 32pistoles au jeu [. . . ].
Extrait de la lettre de Pascal a Fermat du 29 juillet 1654
. Bertrand’s Ballot problemIn combinatorics, Bertrand’s ballot problem (solved in 1878) is thequestion:
In an election where candidate A receives p votes and candidate Breceives q votes with p > q, what is the probability that A will bestrictly ahead of B throughout the count?
The answer isp − q
p + q.
Since when do we count paths?
. Chevalier de Mere’s problemL’impatience me prend aussi bien qu’a vous et, quoique je sois encoreau lit, je ne puis m’empecher de vous dire que [. . . ]. Voici a peu prescomme je fais pour savoir la valeur de chacune des parties, quanddeux joueurs jouent, par exemple, en trois parties, et chacun a mis 32pistoles au jeu [. . . ].
Extrait de la lettre de Pascal a Fermat du 29 juillet 1654
. Bertrand’s Ballot problemIn combinatorics, Bertrand’s ballot problem (solved in 1878) is thequestion:
In an election where candidate A receives p votes and candidate Breceives q votes with p > q, what is the probability that A will bestrictly ahead of B throughout the count?
The answer isp − q
p + q.
50’s, 60’s and 70’s
. Fun with lattice paths, Howard Grossman (1950)
. How many roads, Bob Dylan (1962)
.Sur une classe de problemes lies au treillis despartitions d’entiers, Germain Kreweras (1965)
.An Introduction to Probability Theory and ItsApplications, William Feller (1950–1966)
50’s, 60’s and 70’s
. Fun with lattice paths, Howard Grossman (1950)
. How many roads, Bob Dylan (1962)
.Sur une classe de problemes lies au treillis despartitions d’entiers, Germain Kreweras (1965)
.An Introduction to Probability Theory and ItsApplications, William Feller (1950–1966)
50’s, 60’s and 70’s
. Fun with lattice paths, Howard Grossman (1950)
. How many roads, Bob Dylan (1962)
.Sur une classe de problemes lies au treillis despartitions d’entiers, Germain Kreweras (1965)
.An Introduction to Probability Theory and ItsApplications, William Feller (1950–1966)
50’s, 60’s and 70’s
. Fun with lattice paths, Howard Grossman (1950)
. How many roads, Bob Dylan (1962)
.Sur une classe de problemes lies au treillis despartitions d’entiers, Germain Kreweras (1965)
.An Introduction to Probability Theory and ItsApplications, William Feller (1950–1966)
Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane).
. Example withS = {↙, ←, ↗, →}.
fS(0; 0, 0) = 1fS(2n + 1; 0, 0) = 0fS(2; 0, 0) = 2fS(4; 0, 0) = 11 -
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Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane).
. Example withS = {↙, ←, ↗, →}.
fS(0; 0, 0) = 1fS(2n + 1; 0, 0) = 0fS(2; 0, 0) = 2fS(4; 0, 0) = 11 -
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Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane).
. Example withS = {↙, ←, ↗, →}.
fS(0; 0, 0) = 1fS(2n + 1; 0, 0) = 0fS(2; 0, 0) = 2fS(4; 0, 0) = 11 -
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Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane). Complete generating function
QS(t; x , y) =∞∑
n=0
∞∑i ,j=0
fS(n; i , j)x i y j
tn ∈ Q[x , y ][[t]].
Questions: Given S, what can be said about QS(t; x , y)?Structure? (algebraic/holonomic) Explicit form? Asymptotics?
QS(t; 0, 0) ; counts S-walks returning to the origin (excursions);QS(t; 1, 1) ; counts S-walks with prescribed length.
Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane). Complete generating function
QS(t; x , y) =∞∑
n=0
∞∑i ,j=0
fS(n; i , j)x i y j
tn ∈ Q[x , y ][[t]].
Questions: Given S, what can be said about QS(t; x , y)?Structure? (algebraic/holonomic) Explicit form? Asymptotics?
QS(t; 0, 0) ; counts S-walks returning to the origin (excursions);QS(t; 1, 1) ; counts S-walks with prescribed length.
Context: enumeration of lattice walks
. Nearest-neighbor walks in the plane Z2; admissible steps
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
. S-walks: walks in Z2 starting at (0, 0) and using steps in S.
. fS(n; i , j): number of S-walks ending at (i , j) and consistingof exactly n steps, possibly confined to some subdomain of Z2
(for us: the quarter plane). Complete generating function
QS(t; x , y) =∞∑
n=0
∞∑i ,j=0
fS(n; i , j)x i y j
tn ∈ Q[x , y ][[t]].
Questions: Given S, what can be said about QS(t; x , y)?Structure? (algebraic/holonomic) Explicit form? Asymptotics?
QS(t; 0, 0) ; counts S-walks returning to the origin (excursions);QS(t; 1, 1) ; counts S-walks with prescribed length.
First example: Kreweras walk
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Theorem [Kreweras (1965); 100 pages combinatorial proof!]
QS(t; 0, 0) = 3F2
(1/3 2/3 1
3/2 2
∣∣∣∣ 27 t3
)=∞∑
n=0
4n(3n
n
)(n + 1)(2n + 1)
t3n.
Theorem [Gessel (1986), Bousquet-Melou (2005), . . . ]The trivariate generating function QS(t; x , y) is algebraic.
First example: Kreweras walk
-
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Theorem [Kreweras (1965); 100 pages combinatorial proof!]
QS(t; 0, 0) = 3F2
(1/3 2/3 1
3/2 2
∣∣∣∣ 27 t3
)=∞∑
n=0
4n(3n
n
)(n + 1)(2n + 1)
t3n.
Theorem [Gessel (1986), Bousquet-Melou (2005), . . . ]The trivariate generating function QS(t; x , y) is algebraic.
First example: Kreweras walk
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Theorem [Kreweras (1965); 100 pages combinatorial proof!]
QS(t; 0, 0) = 3F2
(1/3 2/3 1
3/2 2
∣∣∣∣ 27 t3
)=∞∑
n=0
4n(3n
n
)(n + 1)(2n + 1)
t3n.
Theorem [Gessel (1986), Bousquet-Melou (2005), . . . ]The trivariate generating function QS(t; x , y) is algebraic.
Second example: the simple random walk (1/2)
SRW in the plane
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?-� Polya (1921):
. Formula for the excursions
. Rational generating function
SRW in the half-plane and in the quarter-plane
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. Algebraic (Bousquet-Melou and Petkovsek, 2003) and holonomicgenerating functions (Bousquet-Melou and Mishna, 2010),respectively
Second example: the simple random walk (1/2)
SRW in the plane
-
66
?-� Polya (1921):
. Formula for the excursions
. Rational generating function
SRW in the half-plane and in the quarter-plane
-
66
?-�
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66
?-�
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. Algebraic (Bousquet-Melou and Petkovsek, 2003) and holonomicgenerating functions (Bousquet-Melou and Mishna, 2010),respectively
Second example: the simple random walk (2/2)
SRW in the angle 45◦
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. Formula for the excursions (Gouyou-Beauchamps, 1986)
. Holonomic generating function (Bousquet-Melou and Mishna,2010)
What about the SRW in the angle 135◦?
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Second example: the simple random walk (2/2)
SRW in the angle 45◦
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. Formula for the excursions (Gouyou-Beauchamps, 1986)
. Holonomic generating function (Bousquet-Melou and Mishna,2010)
What about the SRW in the angle 135◦?
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Statement of Gessel’s conjecture
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Conjecture [Gessel (2001)]
QS(t; 0, 0) = 3F2
(5/6 1/2 1
5/3 2
∣∣∣∣ 16t2
)=∞∑
n=0
(5/6)n(1/2)n
(5/3)n(2)n(4t)2n.
Opinion in the combinatorics communityThe generating function QS(t; 0, 0) (thus a fortiori QS(t; x , y))is not algebraic.
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
The conjecture is shared (and made public)
Gessel sends the conjecture to Bousquet-Melou (2001)
. Bousquet-Melou and Petkovsek (1998) Linear recurrences withconstant coefficients: the multivariate case (Nature of thegenerating function)
. Bousquet-Melou (2000) Counting walks in the quarter plane(Basis of a new approach for studying walks in the quarter plane,based on functional equation for generating functions)
Denoting the kernel
KS(t; x , y) = xyt[∑
(i ,j)∈S x i y j − 1/t]
,
one has the functional equation
KSQS(t; x , y) =
KSQS(t; x , 0) + KSQS(t; 0, y)− KSQS(t; 0, 0)− xy .
The conjecture is shared (and made public)
Gessel sends the conjecture to Bousquet-Melou (2001)
. Bousquet-Melou and Petkovsek (1998) Linear recurrences withconstant coefficients: the multivariate case (Nature of thegenerating function)
. Bousquet-Melou (2000) Counting walks in the quarter plane(Basis of a new approach for studying walks in the quarter plane,based on functional equation for generating functions)
Denoting the kernel
KS(t; x , y) = xyt[∑
(i ,j)∈S x i y j − 1/t]
,
one has the functional equation
KSQS(t; x , y) =
KSQS(t; x , 0) + KSQS(t; 0, y)− KSQS(t; 0, 0)− xy .
The conjecture is shared (and made public)
Gessel sends the conjecture to Bousquet-Melou (2001)
. Bousquet-Melou and Petkovsek (1998) Linear recurrences withconstant coefficients: the multivariate case (Nature of thegenerating function)
. Bousquet-Melou (2000) Counting walks in the quarter plane(Basis of a new approach for studying walks in the quarter plane,based on functional equation for generating functions)
Denoting the kernel
KS(t; x , y) = xyt[∑
(i ,j)∈S x i y j − 1/t]
,
one has the functional equation
KSQS(t; x , y) =
KSQS(t; x , 0) + KSQS(t; 0, y)− KSQS(t; 0, 0)− xy .
The conjecture is shared (and made public)
Gessel sends the conjecture to Bousquet-Melou (2001)
. Bousquet-Melou and Petkovsek (1998) Linear recurrences withconstant coefficients: the multivariate case (Nature of thegenerating function)
. Bousquet-Melou (2000) Counting walks in the quarter plane(Basis of a new approach for studying walks in the quarter plane,based on functional equation for generating functions)
Denoting the kernel
KS(t; x , y) = xyt[∑
(i ,j)∈S x i y j − 1/t]
,
one has the functional equation
KSQS(t; x , y) =
KSQS(t; x , 0) + KSQS(t; 0, y)− KSQS(t; 0, 0)− xy .
Walks with small steps in the quarter plane (1/2)
Systematic study of walks with small steps in the quarter plane(Bousquet-Melou and Mishna, 2003–2010)
There are 28 models of walks in the quarter plane:
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
Some of these 28 models are:
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trivial, simple, half-plane, symmetrical.
Finally, it remains 79 problems!
Classifying lattice walks restricted to the quarter plane(Mishna, 2003–2009)
Walks with small steps in the quarter plane (1/2)
Systematic study of walks with small steps in the quarter plane(Bousquet-Melou and Mishna, 2003–2010)
There are 28 models of walks in the quarter plane:
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
Some of these 28 models are:
-
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trivial, simple, half-plane, symmetrical.
Finally, it remains 79 problems!
Classifying lattice walks restricted to the quarter plane(Mishna, 2003–2009)
Walks with small steps in the quarter plane (1/2)
Systematic study of walks with small steps in the quarter plane(Bousquet-Melou and Mishna, 2003–2010)
There are 28 models of walks in the quarter plane:
S ⊆ {↙, ←, ↖, ↑, ↗, →, ↘, ↓}.
Some of these 28 models are:
-
6
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6
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trivial, simple, half-plane, symmetrical.
Finally, it remains 79 problems!
Classifying lattice walks restricted to the quarter plane(Mishna, 2003–2009)
Walks with small steps in the quarter plane (2/2)
The group of the walk (Malyshev, 1970)
The polynomial∑(i ,j)∈S x i y j =
∑1i=−1 Bi (y)x i =
∑1j=−1 Aj (x)y j
is left invariant under
ψ(x , y) =
(x ,
A−1(x)
A+1(x)
1
y
), φ(x , y) =
(B−1(y)
B+1(y)
1
x, y
),
and thus under any element of the group⟨ψ,φ
⟩.
Classification of the 79 = 22 + 1 + 56 models(Bousquet-Melou and Mishna, Bostan and Kauers, 2010)
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Order 4 (16) Order 6 (5) Order 8 (2) Order ∞ (56)
Walks with small steps in the quarter plane (2/2)
The group of the walk (Malyshev, 1970)
The polynomial∑(i ,j)∈S x i y j =
∑1i=−1 Bi (y)x i =
∑1j=−1 Aj (x)y j
is left invariant under
ψ(x , y) =
(x ,
A−1(x)
A+1(x)
1
y
), φ(x , y) =
(B−1(y)
B+1(y)
1
x, y
),
and thus under any element of the group⟨ψ,φ
⟩.
Classification of the 79 = 22 + 1 + 56 models(Bousquet-Melou and Mishna, Bostan and Kauers, 2010)
-
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Order 4 (16) Order 6 (5) Order 8 (2) Order ∞ (56)
Walks with small steps in the quarter plane (2/2)
The group of the walk (Malyshev, 1970)
The polynomial∑(i ,j)∈S x i y j =
∑1i=−1 Bi (y)x i =
∑1j=−1 Aj (x)y j
is left invariant under
ψ(x , y) =
(x ,
A−1(x)
A+1(x)
1
y
), φ(x , y) =
(B−1(y)
B+1(y)
1
x, y
),
and thus under any element of the group⟨ψ,φ
⟩.
Classification of the 79 = 22 + 1 + 56 models(Bousquet-Melou and Mishna, Bostan and Kauers, 2010)
-
6
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-
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-
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Order 4 (16) Order 6 (5) Order 8 (2) Order ∞ (56)
Walks with small steps in the quarter plane (2/2)
The group of the walk (Malyshev, 1970)
The polynomial∑(i ,j)∈S x i y j =
∑1i=−1 Bi (y)x i =
∑1j=−1 Aj (x)y j
is left invariant under
ψ(x , y) =
(x ,
A−1(x)
A+1(x)
1
y
), φ(x , y) =
(B−1(y)
B+1(y)
1
x, y
),
and thus under any element of the group⟨ψ,φ
⟩.
Classification of the 79 = 22 + 1 + 56 models(Bousquet-Melou and Mishna, Bostan and Kauers, 2010)
-
6
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-
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-
6-����
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Order 4 (16) Order 6 (5) Order 8 (2) Order ∞ (56)
Walks with small steps in the quarter plane (2/2)
The group of the walk (Malyshev, 1970)
The polynomial∑(i ,j)∈S x i y j =
∑1i=−1 Bi (y)x i =
∑1j=−1 Aj (x)y j
is left invariant under
ψ(x , y) =
(x ,
A−1(x)
A+1(x)
1
y
), φ(x , y) =
(B−1(y)
B+1(y)
1
x, y
),
and thus under any element of the group⟨ψ,φ
⟩.
Classification of the 79 = 22 + 1 + 56 models(Bousquet-Melou and Mishna, Bostan and Kauers, 2010)
-
6
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-
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-
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Order 4 (16) Order 6 (5) Order 8 (2) Order ∞ (56)
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Manuel Kauersand Doron Zeilberger (2008)Illustration by Kreweras walksFirst written appearance of Gessel’sconjecture
No proof of the conjecture
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Kauers and Zeil-berger (2008). Illustration by Kreweras walks. First written appearance of Gessel’sconjecture
. No proof of the conjecture
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Kauers and Zeil-berger (2008)
. Illustration by Kreweras walks
. First written appearance of Gessel’sconjecture
. No proof of the conjecture
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Kauers and Zeil-berger (2008). Illustration by Kreweras walks
. First written appearance of Gessel’sconjecture
. No proof of the conjecture
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Kauers and Zeil-berger (2008). Illustration by Kreweras walks. First written appearance of Gessel’sconjecture
. No proof of the conjecture
January 28, 2008
Two talks in seminar “Algorithms” (Philippe Flajolet’s team)at Inria Paris-Rocquencourt
.Establishing Non-D-finiteness of Combinatorial Generating Functions,
Marni Mishna
.Integration of Algebraic Functions using Grobner Bases, Manuel Kauers
Computer-aided approach to guessand prove recurrence relations.The quasi-holonomic ansatz and re-stricted lattice walks, Kauers and Zeil-berger (2008). Illustration by Kreweras walks. First written appearance of Gessel’sconjecture
. No proof of the conjecture
Summer 2008: proof of Gessel’s conjecture
Proof of Ira Gessel’s lattice path conjecture
(Kauers, Koutschan and Zeilberger)
To that end, D.Z. offers a prize of one hundred (100) US dollars for a short, self-contained, human-generated (andcomputer-free) proof of Gessel’s conjecture, not to exceed five standard pages typed in standard font. The longerthat prize would remain unclaimed, the more (empirical) evidence we would have that a proof of Gessel’sconjecture is indeed beyond the scope of humankind.
The complete generating function for Gessel walks is algebraic
(Bostan and Kauers)
Summer 2008: proof of Gessel’s conjecture
Proof of Ira Gessel’s lattice path conjecture
(Kauers, Koutschan and Zeilberger)
To that end, D.Z. offers a prize of one hundred (100) US dollars for a short, self-contained, human-generated (andcomputer-free) proof of Gessel’s conjecture, not to exceed five standard pages typed in standard font. The longerthat prize would remain unclaimed, the more (empirical) evidence we would have that a proof of Gessel’sconjecture is indeed beyond the scope of humankind.
The complete generating function for Gessel walks is algebraic
(Bostan and Kauers)
Summer 2008: proof of Gessel’s conjecture
Proof of Ira Gessel’s lattice path conjecture
(Kauers, Koutschan and Zeilberger)
To that end, D.Z. offers a prize of one hundred (100) US dollars for a short, self-contained, human-generated (andcomputer-free) proof of Gessel’s conjecture, not to exceed five standard pages typed in standard font. The longerthat prize would remain unclaimed, the more (empirical) evidence we would have that a proof of Gessel’sconjecture is indeed beyond the scope of humankind.
The complete generating function for Gessel walks is algebraic
(Bostan and Kauers)
History of the algebraicity
(waste of time because of the rumor of the non-algebraicity)
. January 28: talk of Manuel Kauers
. February 22: guessed diff. eq. for QS(t; x , 0) and QS(t; 0, y).
I The diff. eq. are huge: degree 11 in ddt , 96 in t, 78 in x , and
integers of 61 decimal digits.
I In principle, sufficient to prove that QS(t; x , y) is holonomic(closure properties of holonomic functions), but problem ofdetermining 1.5 billon integer coefficients. . .
. July 29: testing one more property expected from the operatorkilling QS(t; x , y), a surprising result suggests that the functionsare in fact algebraic!
. August 26: They find vanishing polynomials for the generatingfunctions, and make their result public.
. People were surprised. (Why was the algebraicity of QS(t; 0, 0)not discovered earlier?)
History of the algebraicity
(waste of time because of the rumor of the non-algebraicity)
. January 28: talk of Manuel Kauers
. February 22: guessed diff. eq. for QS(t; x , 0) and QS(t; 0, y).
I The diff. eq. are huge: degree 11 in ddt , 96 in t, 78 in x , and
integers of 61 decimal digits.
I In principle, sufficient to prove that QS(t; x , y) is holonomic(closure properties of holonomic functions), but problem ofdetermining 1.5 billon integer coefficients. . .
. July 29: testing one more property expected from the operatorkilling QS(t; x , y), a surprising result suggests that the functionsare in fact algebraic!
. August 26: They find vanishing polynomials for the generatingfunctions, and make their result public.
. People were surprised. (Why was the algebraicity of QS(t; 0, 0)not discovered earlier?)
History of the algebraicity
(waste of time because of the rumor of the non-algebraicity)
. January 28: talk of Manuel Kauers
. February 22: guessed diff. eq. for QS(t; x , 0) and QS(t; 0, y).
I The diff. eq. are huge: degree 11 in ddt , 96 in t, 78 in x , and
integers of 61 decimal digits.
I In principle, sufficient to prove that QS(t; x , y) is holonomic(closure properties of holonomic functions), but problem ofdetermining 1.5 billon integer coefficients. . .
. July 29: testing one more property expected from the operatorkilling QS(t; x , y), a surprising result suggests that the functionsare in fact algebraic!
. August 26: They find vanishing polynomials for the generatingfunctions, and make their result public.
. People were surprised. (Why was the algebraicity of QS(t; 0, 0)not discovered earlier?)
History of the algebraicity
(waste of time because of the rumor of the non-algebraicity)
. January 28: talk of Manuel Kauers
. February 22: guessed diff. eq. for QS(t; x , 0) and QS(t; 0, y).
I The diff. eq. are huge: degree 11 in ddt , 96 in t, 78 in x , and
integers of 61 decimal digits.
I In principle, sufficient to prove that QS(t; x , y) is holonomic(closure properties of holonomic functions), but problem ofdetermining 1.5 billon integer coefficients. . .
. July 29: testing one more property expected from the operatorkilling QS(t; x , y), a surprising result suggests that the functionsare in fact algebraic!
. August 26: They find vanishing polynomials for the generatingfunctions, and make their result public.
. People were surprised. (Why was the algebraicity of QS(t; 0, 0)not discovered earlier?)
History of the algebraicity
(waste of time because of the rumor of the non-algebraicity)
. January 28: talk of Manuel Kauers
. February 22: guessed diff. eq. for QS(t; x , 0) and QS(t; 0, y).
I The diff. eq. are huge: degree 11 in ddt , 96 in t, 78 in x , and
integers of 61 decimal digits.
I In principle, sufficient to prove that QS(t; x , y) is holonomic(closure properties of holonomic functions), but problem ofdetermining 1.5 billon integer coefficients. . .
. July 29: testing one more property expected from the operatorkilling QS(t; x , y), a surprising result suggests that the functionsare in fact algebraic!
. August 26: They find vanishing polynomials for the generatingfunctions, and make their result public.
. People were surprised. (Why was the algebraicity of QS(t; 0, 0)not discovered earlier?)
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Complex analysis methods
Fayolle, Iasnogorodski and Malyshev (70’s)
An analytical method in the theory of two-dimensional positiverandom walks, Malyshev (1972)Two coupled processors: the reduction to a Riemann-Hilbertproblem, Fayolle and Iasnogorodski (1979)
. Functional equation
. Boundary value problem
. Expression for the generating function in terms of Cauchyintegrals
Kurkova and R. (2009)
Explicit expression for the generating function counting Gessel’swalks, Kurkova and R. (2009)
. Explicit expression
QS(t; x , 0) =
∫Ct
f (t; u)
u − xdu.
Other methods
Petkovsek and Wilf (2008)
On a conjecture of Gessel. Expression of Gessel’s numbers in terms of determinants
Ping (2009)
Proof of two conjectures of Petkovsek and Wilf on Gessel walks. Probabilistic approach of Gessel’s conjecture (reflection principle,etc.)
Ayyer (2009)
Towards a human proof of Gessel’s conjecture. Representation theory and walks on alphabets
Fayolle and R. (2009)
On the holonomy or algebraicity of generating functions countinglattice walks in the quarter plane. Algebraic methods (Galois theory)
Other methods
Petkovsek and Wilf (2008)
On a conjecture of Gessel. Expression of Gessel’s numbers in terms of determinants
Ping (2009)
Proof of two conjectures of Petkovsek and Wilf on Gessel walks. Probabilistic approach of Gessel’s conjecture (reflection principle,etc.)
Ayyer (2009)
Towards a human proof of Gessel’s conjecture. Representation theory and walks on alphabets
Fayolle and R. (2009)
On the holonomy or algebraicity of generating functions countinglattice walks in the quarter plane. Algebraic methods (Galois theory)
Other methods
Petkovsek and Wilf (2008)
On a conjecture of Gessel. Expression of Gessel’s numbers in terms of determinants
Ping (2009)
Proof of two conjectures of Petkovsek and Wilf on Gessel walks. Probabilistic approach of Gessel’s conjecture (reflection principle,etc.)
Ayyer (2009)
Towards a human proof of Gessel’s conjecture. Representation theory and walks on alphabets
Fayolle and R. (2009)
On the holonomy or algebraicity of generating functions countinglattice walks in the quarter plane. Algebraic methods (Galois theory)
Other methods
Petkovsek and Wilf (2008)
On a conjecture of Gessel. Expression of Gessel’s numbers in terms of determinants
Ping (2009)
Proof of two conjectures of Petkovsek and Wilf on Gessel walks. Probabilistic approach of Gessel’s conjecture (reflection principle,etc.)
Ayyer (2009)
Towards a human proof of Gessel’s conjecture. Representation theory and walks on alphabets
Fayolle and R. (2009)
On the holonomy or algebraicity of generating functions countinglattice walks in the quarter plane. Algebraic methods (Galois theory)
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Summary of our approach
Bostan, Kurkova and R. (2013)
A human1 proof of Gessel’s lattice path conjecture
. Finding QS(t; x , y) amounts to finding QS(t; x , 0) andQS(t; 0, y).
. To find the expression of the generating function QS(t; x , 0),find its expressions (its branches, or its Riemman surface).
. A rewriting of the functional equation gives that there is only afinite number of branches and allows to compute the poles of thebranches.
. With the theory of elliptic functions, we obtain an expression ofQS(t; x , 0) in terms of ζ-Weierstrass functions.
. (Relatively) standard identities from the theory of specialfunctions give QS(t; 0; 0) as a sum of hypergeometric functions.
1Of the XIXth century.
Main result (in terms of ζ-Weierstrass functions)
Bostan, Kurkova and R. (2013)
2z2Q(0, 0) =+1ζ(1
3ω3
)−3ζ
(2
3ω3
)+2ζ
(3
3ω3
)+3ζ
(4
3ω3
)−5ζ
(5
3ω3
)+2ζ
(6
3ω3
),
with
I ζ(ω) = 1ω+∑
(n1,n3)∈Z2\(0,0)
(1
ω−(n1ω1+4n3ω3) + 1n1ω1+4n3ω3
+ ω(n1ω1+4n3ω3)2
),
I ω1 = i∫ x2
x1
dx√−d(x)
∈ iR,
I ω3 = 34
∫ 1/x2
x2
dx√d(x)∈ R,
I d(x) = (zx2 − x + z)2 − 4z2x2,
I x1 = 1+2z−√
1+4z2z , x2 = 1−2z−
√1−4z
2z .
Main result (in terms of ζ-Weierstrass functions)
Bostan, Kurkova and R. (2013)
2z2Q(0, 0) =+1ζ(1
3ω3
)−3ζ
(2
3ω3
)+2ζ
(3
3ω3
)+3ζ
(4
3ω3
)−5ζ
(5
3ω3
)+2ζ
(6
3ω3
),
with
I ζ(ω) = 1ω+∑
(n1,n3)∈Z2\(0,0)
(1
ω−(n1ω1+4n3ω3) + 1n1ω1+4n3ω3
+ ω(n1ω1+4n3ω3)2
),
I ω1 = i∫ x2
x1
dx√−d(x)
∈ iR,
I ω3 = 34
∫ 1/x2
x2
dx√d(x)∈ R,
I d(x) = (zx2 − x + z)2 − 4z2x2,
I x1 = 1+2z−√
1+4z2z , x2 = 1−2z−
√1−4z
2z .
Main result (in terms of ζ-Weierstrass functions)
Bostan, Kurkova and R. (2013)
2z2Q(0, 0) =+1ζ(1
3ω3
)−3ζ
(2
3ω3
)+2ζ
(3
3ω3
)+3ζ
(4
3ω3
)−5ζ
(5
3ω3
)+2ζ
(6
3ω3
),
with
I ζ(ω) = 1ω+∑
(n1,n3)∈Z2\(0,0)
(1
ω−(n1ω1+4n3ω3) + 1n1ω1+4n3ω3
+ ω(n1ω1+4n3ω3)2
),
I ω1 = i∫ x2
x1
dx√−d(x)
∈ iR,
I ω3 = 34
∫ 1/x2
x2
dx√d(x)∈ R,
I d(x) = (zx2 − x + z)2 − 4z2x2,
I x1 = 1+2z−√
1+4z2z , x2 = 1−2z−
√1−4z
2z .
Main result (in terms of ζ-Weierstrass functions)
Bostan, Kurkova and R. (2013)
2z2Q(0, 0) =+1ζ(1
3ω3
)−3ζ
(2
3ω3
)+2ζ
(3
3ω3
)+3ζ
(4
3ω3
)−5ζ
(5
3ω3
)+2ζ
(6
3ω3
),
with
I ζ(ω) = 1ω+∑
(n1,n3)∈Z2\(0,0)
(1
ω−(n1ω1+4n3ω3) + 1n1ω1+4n3ω3
+ ω(n1ω1+4n3ω3)2
),
I ω1 = i∫ x2
x1
dx√−d(x)
∈ iR,
I ω3 = 34
∫ 1/x2
x2
dx√d(x)∈ R,
I d(x) = (zx2 − x + z)2 − 4z2x2,
I x1 = 1+2z−√
1+4z2z , x2 = 1−2z−
√1−4z
2z .
Context and statement of Gessel’s lattice path conjecture
The conjecture spreads out and other questions appear
A first (computer-aided) proof
Other approaches, without proof
A human (computer-free) proof
Conclusions
Other Gessel’s conjectures
Other Gessel’s conjectures
Open questions
. Combinatorial proof of Gessel’s conjectureTowards a combinatorial understanding of lattice pathasymptotics, by Johnson, Mishna and Yeats (2013)
. How to win the 100 dollars?
. Combinatorics of walks with big jumps
. Combinatorics of walks with in higher dimensionOn lattice walks confined to the positive octant, byBousquet-Melou, Bostan, Kauers and Melczer
. Link between the finiteness of the group and the nature of thegenerating function
Open questions
. Combinatorial proof of Gessel’s conjectureTowards a combinatorial understanding of lattice pathasymptotics, by Johnson, Mishna and Yeats (2013)
. How to win the 100 dollars?
. Combinatorics of walks with big jumps
. Combinatorics of walks with in higher dimensionOn lattice walks confined to the positive octant, byBousquet-Melou, Bostan, Kauers and Melczer
. Link between the finiteness of the group and the nature of thegenerating function
Open questions
. Combinatorial proof of Gessel’s conjectureTowards a combinatorial understanding of lattice pathasymptotics, by Johnson, Mishna and Yeats (2013)
. How to win the 100 dollars?
. Combinatorics of walks with big jumps
. Combinatorics of walks with in higher dimensionOn lattice walks confined to the positive octant, byBousquet-Melou, Bostan, Kauers and Melczer
. Link between the finiteness of the group and the nature of thegenerating function
Open questions
. Combinatorial proof of Gessel’s conjectureTowards a combinatorial understanding of lattice pathasymptotics, by Johnson, Mishna and Yeats (2013)
. How to win the 100 dollars?
. Combinatorics of walks with big jumps
. Combinatorics of walks with in higher dimensionOn lattice walks confined to the positive octant, byBousquet-Melou, Bostan, Kauers and Melczer
. Link between the finiteness of the group and the nature of thegenerating function
Open questions
. Combinatorial proof of Gessel’s conjectureTowards a combinatorial understanding of lattice pathasymptotics, by Johnson, Mishna and Yeats (2013)
. How to win the 100 dollars?
. Combinatorics of walks with big jumps
. Combinatorics of walks with in higher dimensionOn lattice walks confined to the positive octant, byBousquet-Melou, Bostan, Kauers and Melczer
. Link between the finiteness of the group and the nature of thegenerating function
Merci pour votre attention !
Important classes of univariate power series
Important classes of univariate power series
algebraic
hypergeom
Holonomic series
Holonomic : S(t) ∈ Q[[t]] satisfying a linear differential equationwith polynomial coefficients cr (t)S (r)(t) + · · ·+ c0(t)S(t) = 0.
Algebraic : S(t) ∈ Q[[t]] root of a polynomial P ∈ Q[t, T ].
Hypergeometric : S(t) =∑
n sntn such that sn+1
sn∈ Q(n). E.g.
2F1
(a b
c
∣∣∣∣ t
)=∞∑
n=0
(a)n(b)n
(c)n
tn
n!, (a)n = a(a + 1) · · · (a + n− 1).
Important classes of univariate power series
algebraic
hypergeom
Holonomic series
Holonomic : S(t) ∈ Q[[t]] satisfying a linear differential equationwith polynomial coefficients cr (t)S (r)(t) + · · ·+ c0(t)S(t) = 0.
Algebraic : S(t) ∈ Q[[t]] root of a polynomial P ∈ Q[t, T ].
Hypergeometric : S(t) =∑
n sntn such that sn+1
sn∈ Q(n). E.g.
2F1
(a b
c
∣∣∣∣ t
)=∞∑
n=0
(a)n(b)n
(c)n
tn
n!, (a)n = a(a + 1) · · · (a + n− 1).
Important classes of univariate power series
algebraic
hypergeom
Holonomic series
Holonomic : S(t) ∈ Q[[t]] satisfying a linear differential equationwith polynomial coefficients cr (t)S (r)(t) + · · ·+ c0(t)S(t) = 0.
Algebraic : S(t) ∈ Q[[t]] root of a polynomial P ∈ Q[t, T ].
Hypergeometric : S(t) =∑
n sntn such that sn+1
sn∈ Q(n). E.g.
2F1
(a b
c
∣∣∣∣ t
)=∞∑
n=0
(a)n(b)n
(c)n
tn
n!, (a)n = a(a + 1) · · · (a + n− 1).
Important classes of univariate power series
algebraic
hypergeom
Holonomic series
Holonomic : S(t) ∈ Q[[t]] satisfying a linear differential equationwith polynomial coefficients cr (t)S (r)(t) + · · ·+ c0(t)S(t) = 0.
Algebraic : S(t) ∈ Q[[t]] root of a polynomial P ∈ Q[t, T ].
Hypergeometric : S(t) =∑
n sntn such that sn+1
sn∈ Q(n). E.g.
2F1
(a b
c
∣∣∣∣ t
)=∞∑
n=0
(a)n(b)n
(c)n
tn
n!, (a)n = a(a + 1) · · · (a + n− 1).
Important classes of multivariate power series
algebraic series
Holonomic series
S ∈ Q[[x , y , t]] is holonomic if the set of all partial derivatives of Sspans a finite-dimensional vector space over Q(x , y , t).
S ∈ Q[[x , y , t]] is algebraic if it is the root of a P ∈ Q[x , y , t, T ].
Important classes of multivariate power series
algebraic series
Holonomic series
S ∈ Q[[x , y , t]] is holonomic if the set of all partial derivatives of Sspans a finite-dimensional vector space over Q(x , y , t).
S ∈ Q[[x , y , t]] is algebraic if it is the root of a P ∈ Q[x , y , t, T ].
Main methods for proving holonomy andnon-holonomy
Main methods
(1) for proving non-holonomy
(1a) Infinite number of singularities, or lacunary(1b) Asymptotics
(2) for proving holonomy
(2a) Diagonals, or positive parts, of rational functions(2b) Guess’n’Prove
. All methods are algorithmic.
“Guess and Prove” approach
Methodology for proving algebraicity
Experimental mathematics—Guess’n’Prove—approach:
(S1) high order expansion of the generating series FS(t; x , y);
(S2) guessing candidates for minimal polynomials of FS(t; x , 0)and FS(t; 0, y), based on Hermite-Pade approximation;
(S3) rigorous certification of the minimal polynomials, based on(exact) polynomial computations.